Skew, Kurtosis, and Normality
Describing the shape of a distribution.
The Shape of Data
Beyond the average, every column has a shape. Knowing whether it is symmetric, lopsided, or heavy-tailed changes how you analyze it. 📊
What Skew Means
Skewness measures how lopsided a distribution is. A perfectly symmetric bell has zero skew, while a long tail on one side pushes it positive or negative.
print(df["income"].skew())All lessons in this course
- Correlation Is Not Causation
- Pearson vs Spearman
- Read a Correlation Heatmap
- Skew, Kurtosis, and Normality